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Hugging Face
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add attention mask image for code_llama
1
#472 opened 2 days ago
by
AbhishekRP2002
mishig
updated
a
Space
about 21 hours ago
sbrandeis
updated
a
dataset
about 22 hours ago
Wauplin
updated
a
dataset
1 day ago
manycore-research/SpatialLM-Llama-1B
1
#60 opened 7 days ago
by
sbrandeis
Upload sample-random.txt
#65 opened 2 days ago
by
hapm1
Upload sample-random.txt
#66 opened 2 days ago
by
hapm1
Sylvestre
updated
a
dataset
1 day ago
celinah
updated
a
dataset
2 days ago
Upload cohere-attn-mask
2
#468 opened 6 days ago
by
bimal1109
upload mistral attention mask
5
#471 opened 4 days ago
by
Nahieli777777
Upload 2 files
1
#29 opened 6 days ago
by
ighoyotaachoja4
ByteDance/InfiniteYou
1
#3 opened 7 days ago
by
julien-c
Raiff1982/Codette
1
#61 opened 7 days ago
by
Raiff1982
Qwen/Qwen2.5-Omni-7B
1
#62 opened 7 days ago
by
julien-c
canopylabs/orpheus-3b-0.1-ft
1
#63 opened 7 days ago
by
victor
kashif
updated
a
model
3 days ago
Post
2664
The new DeepSite space is really insane for vibe-coders
enzostvs/deepsite
With the wave of vibe-coding-optimized LLMs like the latest open-source DeepSeek model (version V3-0324), you can basically prompt out-of-the-box and create any app and game in one-shot.
It feels so powerful to me, no more complex framework or under-the-hood prompt engineering to have a working text-to-app tool.
AI is eating the world and *open-source* AI is eating AI itself!
PS: and even more meta is that the DeepSite app and DeepSeek model are both fully open-source code => time to start recursively improve?
PPS: you still need some inference hosting unless you're running the 600B param model at home, so check the very nice list of HF Inference Providers for this model: deepseek-ai/DeepSeek-V3-0324
enzostvs/deepsite
With the wave of vibe-coding-optimized LLMs like the latest open-source DeepSeek model (version V3-0324), you can basically prompt out-of-the-box and create any app and game in one-shot.
It feels so powerful to me, no more complex framework or under-the-hood prompt engineering to have a working text-to-app tool.
AI is eating the world and *open-source* AI is eating AI itself!
PS: and even more meta is that the DeepSite app and DeepSeek model are both fully open-source code => time to start recursively improve?
PPS: you still need some inference hosting unless you're running the 600B param model at home, so check the very nice list of HF Inference Providers for this model: deepseek-ai/DeepSeek-V3-0324
- 1 reply
Post
2092
‼️Sentence Transformers v4.0 is out! You can now train and finetune reranker models with multi-GPU training, bf16 support, loss logging, callbacks & much more. I also prove that finetuning on your domain helps much more than you might think.
1️⃣ Reranker Training Refactor
Reranker models can now be trained using an extensive trainer with a lot of powerful features:
- MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP))
- bf16 training support; loss logging
- Evaluation datasets + evaluation loss
- Improved callback support + an excellent Weights & Biases integration
- Gradient checkpointing, gradient accumulation
- Model card generation
- Resuming from a training checkpoint without performance loss
- Hyperparameter Optimization
and much more!
Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker
Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade.
2️⃣ New Reranker Losses
- 11 new losses:
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
3️⃣ New Reranker Documentation
- New Training Overview, Loss Overview, API Reference docs
- 5 new, 1 refactored training examples docs pages
- 13 new, 6 refactored training scripts
- Migration guides (2.x -> 3.x, 3.x -> 4.x)
4️⃣ Blogpost
Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v4.0.1
1️⃣ Reranker Training Refactor
Reranker models can now be trained using an extensive trainer with a lot of powerful features:
- MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP))
- bf16 training support; loss logging
- Evaluation datasets + evaluation loss
- Improved callback support + an excellent Weights & Biases integration
- Gradient checkpointing, gradient accumulation
- Model card generation
- Resuming from a training checkpoint without performance loss
- Hyperparameter Optimization
and much more!
Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker
Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade.
2️⃣ New Reranker Losses
- 11 new losses:
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
3️⃣ New Reranker Documentation
- New Training Overview, Loss Overview, API Reference docs
- 5 new, 1 refactored training examples docs pages
- 13 new, 6 refactored training scripts
- Migration guides (2.x -> 3.x, 3.x -> 4.x)
4️⃣ Blogpost
Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v4.0.1
freddyaboulton
posted
an
update
9 days ago
Post
1298
Ever wanted to share your AI creations with friends? ✨
Screenshots are fine, but imagine letting others play with your ACTUAL model!
Introducing Gradio deep links 🔗 - now you can share interactive AI apps, not just images.
Add a gr.DeepLinkButton to any app and get shareable URLs that let ANYONE experiment with your models.
Screenshots are fine, but imagine letting others play with your ACTUAL model!
Introducing Gradio deep links 🔗 - now you can share interactive AI apps, not just images.
Add a gr.DeepLinkButton to any app and get shareable URLs that let ANYONE experiment with your models.